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Muck Rack 6 months ago
location: remoteus
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Title: Senior Machine Learning Engineer

Location: Remote

Job Description:

Muck Rack is the leading SaaS platform for public relations and communications professionals. Our mission is to enable organizations to build trust, tell their stories and demonstrate the unique value of earned media. Muck Rack’s Public Relations Management (PRM) platform enables organizations to build relationships with the media, manage crisis risk and demonstrate PR’s impact on business outcomes.

Founder controlled, fully distributed, and growing sustainably, Muck Rack has received several awards for its unparalleled culture and product from organizations like Inc., Quartz, G2, and BuiltIn. We value resilience, transparency, ownership, & customer devotion and infuse these values into everything we do.

We’re looking for a Senior Machine Learning Engineer to join our quickly growing team and make a big impact.

As a Senior Machine Learning Engineer in the Tech org, you’ll work closely with data scientists, software engineers, product managers, and designers, to develop Machine Learning technologies which help simplify the jobs of our users. You’ll work on major technical projects with large data volumes, lead the building of new features, and help shape our engineering culture and processes. Our technology team is focused on scale, quality, delivery, and thoughtful customer experience.

To be set up for success in this role, you’ll need to have:

  • 5+ years total professional experience building Machine Learning products within user-facing software apps
  • A capacity for a high degree of autonomy and out-of-the-box thinking
  • A commitment to collaborating closely with other engineers and across functions

If any of the below also describe you, this could be an exciting opportunity:

  • Worked on a complex, high-traffic site at a startup or software-as-a-service company, ideally with large amounts of data
  • Experience with text modeling, NLP, and large language models
  • Experience serving GPU-intensive models in large-scale production environments
  • Interest in search
  • Interest in journalism, news, media or social media

In addition, we’re always looking for candidates who:

  • Perform an analysis to make a recommendation to other team members as to whether machine learning technologies can be used to solve a given problem, and how best to integrate the technologies with the rest of Muck Rack’s application ecosystem
  • Research and evaluate new ML Engineering methodologies, approaches, and solutions
  • Test, deploy, and monitor supervised or unsupervised learning models
  • Write queries (SQL, elastic search) to grab the right set of data to solve their problem
  • Build tools to enable other data scientists to scale their knowledge and increase impact
  • Interpret and communicate analytic results to analytical and non-analytical business partners and executive decision makers
  • Participate in code reviews and model reviews of their teammates

Interview Overview

Below you’ll find an outline of the interview plan for this role. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

  • 30 min interview with a member of our Talent Team
  • 1 hour zoom interview with the hiring manager
  • Take-home coding assignment (2 hours max)
  • Peer interviews, including a 30 min code review discussion
  • Final call(s) with executive team member(s)

Salary

The starting salary for this role is between $140,000 – $170,000, depending on skills and experience. We take a geo-neutral approach to compensation within the US, meaning that we pay based on job function and level, not location. For all other countries, we have competitive pay bands based on market standards.

Inidual compensation decisions are based on a number of factors, including experience level, skillset, and balancing internal equity relative to peers at the company. We expect the majority of the candidates who are offered roles at our company to fall healthily throughout the range based on these factors. We recognize that the person we hire may be less experienced (or more senior) than this job description as posted. If that ends up being the case, the updated salary range will be communicated with you as a candidate.

Why Muck Rack?

Remote Work, Forever. We’re a fully distributed team and have pledged to remain that way forever. We offer employees a full home office setup, phone & internet reimbursement, and a monthly coworking membership. We build culture through virtual and in-person team bonding opportunities including team lunches, friendly competitions, and celebratory events!

Transparent Compensation. We offer competitive geo-neutral pay in the U.S. and review compensation at least once annually to ensure internal equity and alignment with the external market. Depending on the role, we offer either a standardized bonus program or attainable commission structure and an opportunity to earn equity in the company. All employees are eligible for our 401(k) plan* with employer contributions.

Health & Wellness*. Muck Rack provides comprehensive health, dental, vision, disability and life insurance for employees and their families. We offer a high-deductible health plan with 100% premium coverage for iniduals, as well as a range of other plan options. Our team also has access to 24/7 Virtual Care, an Employee Assistance Program, employer-funded HSA contributions, and other pre-tax benefits. Team members have access to a quarterly wellness stipend and a free Headspace subscription.

PTO and Family Benefits. Our team enjoys 4+ weeks of off-the-grid PTO, paid sick/mental health days and 13 paid holidays, which can be exchanged for additional PTO with our “Holiday Swap Program.” We also provide up to 16 weeks of fully paid parental leave.

Personal & Professional Development. We grow talent by creating internal pathways for advancement and promotion. Muck Rack conducts bi-annual performance reviews, hosts team-wide workshops, and offers management training and leadership training opportunities. We also provide unlimited subscriptions to L&D platforms including Coursera & O’Reilly, as well as 2 additional days of PTO to dedicate to learning and development.

Culture of Inclusion. We know that erse perspectives breed innovation and help us better serve our customers. We are committed to ensuring employees feel their identities are valued and that people of all backgrounds and points of view are treated equitably.

Customer-First. Founder-controlled means we have the freedom to be nimble, highly collaborative and innovative, building forward-thinking products that enable 3,000+ companies around the world to build trust, tell their stories and demonstrate the unique value of earned media.

*These benefits are specific to US-based employees. In some, but not all, cases we are able to offer equivalent benefits to employees located outside of the United States.

While we are a fully distributed team, we do have limitations on where we can hire and maintain a list of acceptable working locations based on job function. If we are unable to hire in your current location for the role for which you applied, you will be notified via email. While we enjoy many benefits as a permanently distributed and remote company, we cannot always support relocation or extended travel and have guidelines in place to ensure compliant work away from your designated permanent residence.

If you’re excited about an opportunity at Muck Rack but your experience doesn’t align perfectly with the requirements of the role outlined here, please don’t let it stop you from applying. We’re committed to building a erse and inclusive workplace, and we want to hear from you. You may be a great fit for this role or another position on our team. We deliberately encourage iniduals from all backgrounds, including race, gender identity, sexual orientation, and disability status to apply for positions. We are an equal opportunity employer and we’re committed to a fair and consistent interview process and candidate experience.

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